Description
Pretrained ALBERT Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. albert-base-japanese-v1
is a Japanese model orginally trained by ken11
.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = AlbertEmbeddings.pretrained("albert_embeddings_albert_base_japanese_v1","ja") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["私はSpark NLPを愛しています"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val embeddings = AlbertEmbeddings.pretrained("albert_embeddings_albert_base_japanese_v1","ja")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("私はSpark NLPを愛しています").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("ja.embed.albert_base_japanese_v1").predict("""私はSpark NLPを愛しています""")
Model Information
Model Name: | albert_embeddings_albert_base_japanese_v1 |
Compatibility: | Spark NLP 3.4.2+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [sentence, token] |
Output Labels: | [bert] |
Language: | ja |
Size: | 45.6 MB |
Case sensitive: | false |
References
- https://huggingface.co/ken11/albert-base-japanese-v1
- https://ken11.jp/blog/sentencepiece-tokenizer-bug
- https://ja.wikipedia.org/wiki/Wikipedia:%E3%83%87%E3%83%BC%E3%82%BF%E3%83%99%E3%83%BC%E3%82%B9%E3%83%80%E3%82%A6%E3%83%B3%E3%83%AD%E3%83%BC%E3%83%89
- https://www.rondhuit.com/download.html#ldcc
- https://github.com/google/sentencepiece
- https://opensource.org/licenses/MIT